Frequency and distribution of AP-1 sites in the human genome

The AP-1-binding sequences are promoter/enhancer elements that play an essential role in the induction of many genes in mammalian cells; however, the number of genes containing AP-1 sites remains unknown. In order to better address the overall effect of AP-1 on expression of genes encoded by the entire genome, a genome-wide analysis of the frequency and distribution of AP-1 sites would be useful; yet to date, no such analysis of AP-1 sites or any other promoter/enhancer elements has been performed. We present here our study of the consensus AP-1 site and two single-bp variants showing that the frequency of AP-1 sites in promoter regions is significantly lower than their average rate of occurrence in the whole genomic sequence, as well as the frequency of a random heptanucleotide suggesting that nature has selected for a decrease in the frequency of AP-1 sites in the regulatory regions of genes. In addition, genes containing multiple AP-1 sites are more prevalent than those containing only one copy of an AP-1 site, which again may have evolved to allow for greater signal amplification or integration in the regulation of AP-1 target genes. However, the number of AP-1-regulated genes identified in various studies is far smaller than the number of genes containing potential AP-1 sites, indicating that not all AP-1 sites are activated in a given cell under a given condition, and is consistent with the prediction by others that cellular context determines which AP-1 sites are targeted by AP-1

Determinants that control the specific interactions between TAB1 and p38α

Previous studies have revealed that transforming growth factor-beta-activated protein kinase 1 (TAB1) interacts with p38 alpha and induces p38 alpha autophosphorylation. Here, we examine the sequence requirements in TAB1 and p38 alpha that drive their interaction. Deletion and point mutations in TAB1 reveal that a proline residue in the C terminus of TAB1 (Pro412) is necessary for its interaction with p38 alpha. Furthermore, a cryptic D-domain-like docking site was identified adjacent to the N terminus of Pro412, putting Pro412 in the (phi(B)+3 position of the docking site. Through mutational analysis, we found that the previously identified hydrophobic docking groove in p38 alpha is involved in this interaction, whereas the CD domain and ED domain are not. Furthermore, chimeric analysis with p38 beta (which does not bind to TAB1) revealed a previously unidentified locus of p38 alpha comprising Thr218 and Ile275 that is essential for specific binding of p38 alpha to TAB1. Converting either of these residues to the corresponding amino acid of p380 abolishes p38 alpha interaction with TAB1. These p38a mutants still can be fully activated by p38 alpha upstream activating kinase mitogen-activated protein kinase kinase 6, but their basal activity and activation in response to some extracellular stimuli are reduced. Adjacent to Thr218 and Ile275 is a site where large conformational changes occur in the presence of docking-site peptides derived from p38 alpha substrates and activators. This suggests that TAB1-induced autophosphorylation of p38 alpha results from conformational changes that are similar but unique to those seen in p38 alpha interactions with its substrates and activating kinases

Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files

Discovery proteomics has limited quantification capabilities because of stochastic precursor-ion selection. Several data-independent acquisition (DIA) methods have been proposed to overcome this limitation1, 2, 3, 4, including the sequential-window acquisition of all theoretical mass spectra (SWATH-MS)4.the National Science Foundation (NSF) of China (grants 91429301 and 31221065), 973 Program 2015CB553800, National Major Project 2013ZX10002-002, 111 Project B12001, funding from Xiamen City (grant 3502Z20130027) and the NSF of China for Fostering Talents in Basic Research (grant J1310027)

Impaired microRNA processing causes corpus luteum insufficiency and infertility in mice

The microRNA (miRNA) processing enzyme Dicer1 is required for zygotic and embryonic development, but the early embryonic lethality of Dicer1 null alleles in mice has limited our ability to address the role of Dicer1 in normal mouse growth and development. To address this question, we used a mouse mutant with a hypomorphic Dicer1 allele (Dicer(d/d)) and found that Dicer1 deficiency resulted in female infertility. This defect in female Dicer(d/d) mice was caused by corpus luteum (CL) insufficiency and resulted, at least in part, from the impaired growth of new capillary vessels in the ovary. We found that the impaired CL angiogenesis in Dicer(d/d) mice was associated with a lack of miR17-5p and let7b, 2 miRNAs that participate in angiogenesis by regulating the expression of the antiangiogenic factor tissue inhibitor of metalloproteinase 1. Furthermore, injection of miR17-5p and let7b into the ovaries of Dicer(d/d) mice partially normalized tissue inhibitor of metalloproteinase 1 expression and CL angiogenesis. Our data indicate that the development and function of the ovarian CL is a physiological process that appears to be regulated by miRNAs and requires Dicer1 function

Pediatric obstructive sleep apnea diagnosis: leveraging machine learning with linear discriminant analysis

ObjectiveThe objective of this study was to investigate the effectiveness of a machine learning algorithm in diagnosing OSA in children based on clinical features that can be obtained in nonnocturnal and nonmedical environments.Patients and methodsThis study was conducted at Beijing Children's Hospital from April 2018 to October 2019. The participants in this study were 2464 children aged 3–18 suspected of having OSA who underwent clinical data collection and polysomnography(PSG). Participants’ data were randomly divided into a training set and a testing set at a ratio of 8:2. The elastic net algorithm was used for feature selection to simplify the model. Stratified 10-fold cross-validation was repeated five times to ensure the robustness of the results.ResultsFeature selection using Elastic Net resulted in 47 features for AHI ≥5 and 31 features for AHI ≥10 being retained. The machine learning model using these selected features achieved an average AUC of 0.73 for AHI ≥5 and 0.78 for AHI ≥10 when tested externally, outperforming models based on PSG questionnaire features. Linear Discriminant Analysis using the selected features identified OSA with a sensitivity of 44% and specificity of 90%, providing a feasible clinical alternative to PSG for stratifying OSA severity.ConclusionsThis study shows that a machine learning model based on children's clinical features effectively identifies OSA in children. Establishing a machine learning screening model based on the clinical features of the target population may be a feasible clinical alternative to nocturnal OSA sleep diagnosis

Spatiotemporal dynamics and functional characteristics of the composition of the main fungal taxa in the root microhabitat of Calanthe sieboldii (Orchidaceae)

Abstract Background Endophytic fungi play a critical ecological role in the growth and development of orchids, but little is known about the spatial and temporal dynamics of fungal diversity or the ecological functions of fungi during orchid growth and reproduction. Calanthe sieboldii Decne. is listed in the Chinese National Key Protected Wild Plants as a class I protected wild plant. To understand the community characteristics of root and soil fungi of the orchid during its reproductive seasons, we investigated the community composition, spatial and temporal dynamics, and functional characteristics of the orchid microhabitat fungi by using diversity and ecological functional analyses. Results We discovered that there were three, seven, and four dominant fungal families in the orchid's roots, rhizoplane soil, and rhizosphere soil, respectively. Tulasnellaceae, Aspergillaceae, and Tricholomataceae were the dominant fungi in this endangered orchid's microhabitats. The closer the fungal community was to the orchid, the more stable and the less likely the community composition to change significantly over time. The fungal communities of this orchid's roots and rhizoplane soil varied seasonally, while those of the rhizosphere soil varied interannually. Saprophytic fungi were the most abundant in the orchid's fungal community, and the closer the distance to the orchid, the more symbiotic fungi were present. Conclusions The fungi in different parts of the root microhabitat of C. sieboldii showed different spatiotemporal dynamic patterns. The fungal community near the orchid roots was relatively stable and displayed seasonal variation, while the community further away from the roots showed greater variation. In addition, compared with the soil fungi, the dominant endophytic fungi were more stable, and these may be key fungi influencing orchid growth and development. Our study on the spatiotemporal dynamics and functions of fungi provides a basis for the comprehensive understanding and utilization of orchid endophytic fungi

Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion

Millimeter-wave interferometric synthetic aperture radiometer (InSAR) can provide high-resolution observations for many applications by using small antennas to achieve very large synthetic aperture. However, reconstruction of a millimeter-wave InSAR image has been proven to be an ill-posed inverse problem that degrades the performance of InSAR imaging. In this paper, a novel millimeter-wave InSAR image reconstruction approach, referred to as InSAR-TVMC, by total variation (TV) regularized matrix completion (MC) in two-dimensional data space, is proposed. Based on the a priori knowledge that natural millimeter-wave images statistically hold the low-rank property, the proposed approach represents the object images as low-rank matrices and formulates the data acquisition of InSAR in two-dimensional data space directly to undersample visibility function samples. Subsequently, using the undersampled visibility function samples, the optimal solution of the InSAR image reconstruction problem is obtained by simultaneously adopting MC techniques and TV regularization. Experimental results on simulated and real millimeter-wave InSAR image data demonstrate the effectiveness and the significant improvement of the reconstruction performance of the proposed InSAR-TVMC approach over conventional and one-dimensional sparse InSAR image reconstruction approaches

Inhibition of defect-induced α-to-δ phase transition for efficient and stable formamidinium perovskite solar cells

Abstract Defects passivation is widely devoted to improving the performance of formamidinium lead triiodide perovskite solar cells; however, the effect of various defects on the α-phase stability is still unclear. Here, using density functional theory, we first reveal the degradation pathway of the formamidinium lead triiodide perovskite from α to δ phase and investigate the effect of various defects on the energy barrier of phase transition. The simulation results predict that iodine vacancies are most likely to trigger the degradation, since they obviously reduce the energy barrier of α-to-δ phase transition and have the lowest formation energies at the perovskite surface. A water-insoluble lead oxalate compact layer is introduced on the perovskite surface to largely suppress the α-phase collapse through hindering the iodine migration and volatilization. Furthermore, this strategy largely reduces the interfacial nonradiative recombination and boosts the efficiency of the solar cells to 25.39% (certified 24.92%). Unpackaged device can maintain 92% of its initial efficiency after operation at maximum power point under simulated air mass 1.5 G irradiation for 550 h